This thesis report describes the elaboration of travel forecast model for strategic planning in urban transportation. The model conception intends to incorporate the spatial – temporal interaction between land use and transportation system as an essential element to quantify trips for future scenarios. In this sense, it is explored Neural Networks to represent such interaction and Geographical Information Systems and Remote Sensing potential to obtain and manipulate geographical – spatial data.